The Department offers the following programs at undergraduate level:
- General Degree (3 years)
- Special Degree in Statistics (4 years)
B.Sc. (General) degree
First year
Semester 1
| STA 113 2.0 | Descriptive Statistics | c |
| STA 114 2.0 | Probability and Distribution Theory I | c |
| STA 115 1.0 | Elements of Sampling | c |
Semester 2
| STA 123 2.0 | Probability and Distribution Theory II | c |
| STA 124 2.0 | Data Analysis I | c |
| STA 125 1.0 | Statistical Communication | c |
Second year
Semester 1
| STA 213 2.0 | Inferential Statistics | c |
| STA 214 1.0 | Nonparametric Statistics | c |
| STA 215 2.0 | Sampling Techniques | c |
Semester 2
| STA 224 2.0 | Regression Analysis | c |
| STA 225 2.0 | Design of Experiments | c |
| STA 226 1.0 | Data Analysis II | c |
Third year
Semester 1
| STA 312 2.0 | Time series analysis | c |
| STA 313 2.0 | Statistical decision theory | o |
| STA 314 2.0 | Multivariate statistical methods | o |
| STA 316 2.0 | Discrete and categorical data analysis | c |
| STA 319 2.0 | Advanced regression analysis | o |
| STA 326 2.0 | Programming and data analysis with R | o |
| STA 351 2.0 | Research methodology | o |
Semester 2
| STA 315 2.0 | Essential skills in statistics | c |
| STA 321 2.0 | Statistical quality assurance | o |
| STA 322 2.0 | Medical statistics | o |
| STA 324 2.0 | Operations research | o |
| STA 325 2.0 | Independent study | o# |
| STA 330 2.0 | Data analysis and preparation of reports | c |
| STA 332 2.0 | Compilation of official statistics | o* |
| STA 333 2.0 | Econometric models | o** |
o#: B.Sc. (general) degree students who have followed STA 351 2.0 Research Methodology can do this course as an optional course
o*: Those who are doing Econometrics as a subject are not allowed to do this course
0**: those who are following B.Sc. (special) degree in Statistics are not allowed to do this course
B.Sc. (special) degree
Part 1
Semester 1
| STA 312 2.0 | Time series analysis | c |
| STA 313 1.0 | Statistical decision theory | c |
| STA 314 2.0 | Multivariate statistical methods | c |
| STA 316 2.0 | Discrete and categorical data analysis | c |
| STA 318 2.0 | Advanced distribution theory | c |
| STA 319 2.0 | Advanced regression analysis | c |
| STA 326 2.0 | Programming and data analysis with R | c |
| STA 351 2.0 | Research methodology | c |
| STA 354 2.0 | Machine learning 1 | o |
Semester 2
| STA 315 2.0 | Essential skills in statistics | c |
| STA 317 2.0 | Advanced design of experiments | c |
| STA 321 2.0 | Statistical quality assurance | c |
| STA 322 2.0 | Medical statistics | o |
| STA 323 2.0 | Introduction to actuarial statistics | o |
| STA 324 2.0 | Operations research | o |
| STA 327 2.0 | Theory of multivariate statistics | c |
| STA 329 2.0 | Advanced statistical inference | c |
| STA 330 2.0 | Data analysis and preparation of reports | c |
| STA 331 2.0 | Stochastic processes | c |
| STA 332 2.0 | Compilation of official statistics | o |
| STA 355 2.0 | Optimization | o |
B.Sc. (special) degree
Part 2
| STA 471 2.0 | Generalized linear and non linear models | c |
| STA 472 2.0 | Special topics in statistics | o |
| STA 474 2.0 | Statistical consultancy | c |
| STA 476 2.0 | Statistical data mining | c |
| STA 477 2.0 | Spatial statistics | o |
| STA 478 2.0 | Advanced time series analysis | c |
| STA 479 2.0 | Advanced sampling theory | c |
| STA 480 2.0 | Current topics in statistics | o |
| STA 481 2.0 | Seminar | c |
| STA 483 6.0 | Research project | c |
| STA 484 4.0 | Internship | c |
| STA 485 2.0 | Measure theory | o |
| STA 486 2.0 | Survival analysis | o |
| STA 487 2.0 | Computational inference | o |
| STA 490 2.0 | Linear mixed models and generalized linear mixed models | c |
| STA 491 2.0 | Bayesian inference | o |